The present invention relates generally to a corpus curation method for cognitive robots, and more particularly, but not by way of limitation, to a system, method, and recording medium for mapping a corpus to link kinematics for robots to the content of the corpus.
Conventionally, corpus creation for cognitive systems is based on various methods. For example, in topic-oriented cognitive systems, every subsection with topic is broken to the lowest level, processed and tagged, while in context-oriented systems the corpus is “cherry-picked” from the content. Such processed corpus is manifested to the user during interaction. While this may be suitable for user interface-based learning purposes, for Robot-based interactions (e.g., tangible and intangible interfaces) this is not suitable. A Cognitive Robot is expected to portray a number of voluntary and involuntary actions along with the content.
For example, gestures, movements like raising hand, turning head etc. of a robot are not tied to the corpus but arbitrarily selected based on the programmer's intuition and preference to link certain moves to certain sections of the response.
Conventional techniques use inline programming such that each change (i.e., add/update/delete) in non-default animations requires re-tagging of all responses.
That is, there is a technical problem in the conventional techniques in that the gestures, movements, responses of a robot are mapped to individual responses or words such that the robots responses can be limited. In addition, each response needs to be re-mapped based on a change for one type of movement to a word, which can result in hundreds of thousands of changes.